ES|QL functions and operators

The STATS ... BY command supports these aggregate functions:

Syntax

AVG(expression)

Description

The average of a numeric expression.

Supported types

The result is always a double no matter the input type.

Examples

FROM employees
| STATS AVG(height)

The expression can use inline functions. For example, to calculate the average over a multivalued column, first use MV_AVG to average the multiple values per row, and use the result with the AVG function:

FROM employees
| STATS avg_salary_change = ROUND(AVG(MV_AVG(salary_change)), 10)

Syntax

COUNT([expression])

Parameters

Description

Returns the total number (count) of input values.

Supported types

Can take any field type as input.

Examples

FROM employees
| STATS COUNT(height)

To count the number of rows, use COUNT() or COUNT(*):

FROM employees
| STATS count = COUNT(*) BY languages
| SORT languages DESC

The expression can use inline functions. This example splits a string into multiple values using the SPLIT function and counts the values:

ROW words="foo;bar;baz;qux;quux;foo"
| STATS word_count = COUNT(SPLIT(words, ";"))

Syntax

COUNT_DISTINCT(expression[, precision_threshold])

Parameters

Description

Returns the approximate number of distinct values.

Supported types

Can take any field type as input.

Examples

FROM hosts
| STATS COUNT_DISTINCT(ip0), COUNT_DISTINCT(ip1)

With the optional second parameter to configure the precision threshold:

FROM hosts
| STATS COUNT_DISTINCT(ip0, 80000), COUNT_DISTINCT(ip1, 5)

The expression can use inline functions. This example splits a string into multiple values using the SPLIT function and counts the unique values:

ROW words="foo;bar;baz;qux;quux;foo"
| STATS distinct_word_count = COUNT_DISTINCT(SPLIT(words, ";"))

Computing exact counts requires loading values into a set and returning its size. This doesn’t scale when working on high-cardinality sets and/or large values as the required memory usage and the need to communicate those per-shard sets between nodes would utilize too many resources of the cluster.

This COUNT_DISTINCT function is based on the HyperLogLog++ algorithm, which counts based on the hashes of the values with some interesting properties:

For a precision threshold of c, the implementation that we are using requires about c * 8 bytes.

The following chart shows how the error varies before and after the threshold:

For all 3 thresholds, counts have been accurate up to the configured threshold. Although not guaranteed, this is likely to be the case. Accuracy in practice depends on the dataset in question. In general, most datasets show consistently good accuracy. Also note that even with a threshold as low as 100, the error remains very low (1-6% as seen in the above graph) even when counting millions of items.

The HyperLogLog++ algorithm depends on the leading zeros of hashed values, the exact distributions of hashes in a dataset can affect the accuracy of the cardinality.

The COUNT_DISTINCT function takes an optional second parameter to configure the precision threshold. The precision_threshold options allows to trade memory for accuracy, and defines a unique count below which counts are expected to be close to accurate. Above this value, counts might become a bit more fuzzy. The maximum supported value is 40000, thresholds above this number will have the same effect as a threshold of 40000. The default value is 3000.

Syntax

MAX(expression)

Parameters

Description

Returns the maximum value of a numeric expression.

Example

FROM employees
| STATS MAX(languages)

The expression can use inline functions. For example, to calculate the maximum over an average of a multivalued column, use MV_AVG to first average the multiple values per row, and use the result with the MAX function:

FROM employees
| STATS max_avg_salary_change = MAX(MV_AVG(salary_change))

Syntax

MEDIAN(expression)

Parameters

Description

Returns the value that is greater than half of all values and less than half of all values, also known as the 50% PERCENTILE.

Example

FROM employees
| STATS MEDIAN(salary), PERCENTILE(salary, 50)

The expression can use inline functions. For example, to calculate the median of the maximum values of a multivalued column, first use MV_MAX to get the maximum value per row, and use the result with the MEDIAN function:

FROM employees
| STATS median_max_salary_change = MEDIAN(MV_MAX(salary_change))

Syntax

MEDIAN_ABSOLUTE_DEVIATION(expression)

Parameters

Description

Returns the median absolute deviation, a measure of variability. It is a robust statistic, meaning that it is useful for describing data that may have outliers, or may not be normally distributed. For such data it can be more descriptive than standard deviation.

It is calculated as the median of each data point’s deviation from the median of the entire sample. That is, for a random variable X, the median absolute deviation is median(|median(X) - X|).

Example

FROM employees
| STATS MEDIAN(salary), MEDIAN_ABSOLUTE_DEVIATION(salary)

The expression can use inline functions. For example, to calculate the the median absolute deviation of the maximum values of a multivalued column, first use MV_MAX to get the maximum value per row, and use the result with the MEDIAN_ABSOLUTE_DEVIATION function:

FROM employees
| STATS m_a_d_max_salary_change = MEDIAN_ABSOLUTE_DEVIATION(MV_MAX(salary_change))

Syntax

MIN(expression)

Parameters

Description

Returns the minimum value of a numeric expression.

Example

FROM employees
| STATS MIN(languages)

The expression can use inline functions. For example, to calculate the minimum over an average of a multivalued column, use MV_AVG to first average the multiple values per row, and use the result with the MIN function:

FROM employees
| STATS min_avg_salary_change = MIN(MV_AVG(salary_change))

Syntax

PERCENTILE(expression, percentile)

Parameters

Description

Returns the value at which a certain percentage of observed values occur. For example, the 95th percentile is the value which is greater than 95% of the observed values and the 50th percentile is the MEDIAN.

Example

FROM employees
| STATS p0 = PERCENTILE(salary,  0)
     , p50 = PERCENTILE(salary, 50)
     , p99 = PERCENTILE(salary, 99)

The expression can use inline functions. For example, to calculate a percentile of the maximum values of a multivalued column, first use MV_MAX to get the maximum value per row, and use the result with the PERCENTILE function:

FROM employees
| STATS p80_max_salary_change = PERCENTILE(MV_MAX(salary_change), 80)

There are many different algorithms to calculate percentiles. The naive implementation simply stores all the values in a sorted array. To find the 50th percentile, you simply find the value that is at my_array[count(my_array) * 0.5].

Clearly, the naive implementation does not scale — the sorted array grows linearly with the number of values in your dataset. To calculate percentiles across potentially billions of values in an Elasticsearch cluster, approximate percentiles are calculated.

The algorithm used by the percentile metric is called TDigest (introduced by Ted Dunning in Computing Accurate Quantiles using T-Digests).

When using this metric, there are a few guidelines to keep in mind:

The following chart shows the relative error on a uniform distribution depending on the number of collected values and the requested percentile:

It shows how precision is better for extreme percentiles. The reason why error diminishes for large number of values is that the law of large numbers makes the distribution of values more and more uniform and the t-digest tree can do a better job at summarizing it. It would not be the case on more skewed distributions.

Calculate the spatial centroid over a field with spatial point geometry type.

FROM airports
| STATS centroid=ST_CENTROID_AGG(location)

Supported types:

Syntax

SUM(expression)

Description

Returns the sum of a numeric expression.

Example

FROM employees
| STATS SUM(languages)

The expression can use inline functions. For example, to calculate the sum of each employee’s maximum salary changes, apply the MV_MAX function to each row and then sum the results:

FROM employees
| STATS total_salary_changes = SUM(MV_MAX(salary_change))

Syntax

VALUES(expression)

Description

Returns all values in a group as a multivalued field. The order of the returned values isn’t guaranteed. If you need the values returned in order use MV_SORT.

Example

  FROM employees
| EVAL first_letter = SUBSTRING(first_name, 0, 1)
| STATS first_name=MV_SORT(VALUES(first_name)) BY first_letter
| SORT first_letter

The STATS ... BY command supports these grouping functions:

Syntax

BUCKET(expression, buckets, from, to)

Parameters

Description

Creates human-friendly buckets and returns a value for each row that corresponds to the resulting bucket the row falls into.

BUCKET can work in two modes: one in which the size of the bucket is computed based on a buckets count recommendation (four parameters) and a range, and another in which the bucket size is provided directly (two parameters).

Using a target number of buckets, a start of a range, and an end of a range, BUCKET picks an appropriate bucket size to generate the target number of buckets or fewer. For example, asking for at most 20 buckets over a year results in monthly buckets:

FROM employees
| WHERE hire_date >= "1985-01-01T00:00:00Z" AND hire_date < "1986-01-01T00:00:00Z"
| STATS hire_date = MV_SORT(VALUES(hire_date)) BY month = BUCKET(hire_date, 20, "1985-01-01T00:00:00Z", "1986-01-01T00:00:00Z")
| SORT hire_date

The goal isn’t to provide exactly the target number of buckets, it’s to pick a range that people are comfortable with that provides at most the target number of buckets.

Combine BUCKET with an aggregation to create a histogram:

FROM employees
| WHERE hire_date >= "1985-01-01T00:00:00Z" AND hire_date < "1986-01-01T00:00:00Z"
| STATS hires_per_month = COUNT(*) BY month = BUCKET(hire_date, 20, "1985-01-01T00:00:00Z", "1986-01-01T00:00:00Z")
| SORT month

Asking for more buckets can result in a smaller range. For example, asking for at most 100 buckets in a year results in weekly buckets:

FROM employees
| WHERE hire_date >= "1985-01-01T00:00:00Z" AND hire_date < "1986-01-01T00:00:00Z"
| STATS hires_per_week = COUNT(*) BY week = BUCKET(hire_date, 100, "1985-01-01T00:00:00Z", "1986-01-01T00:00:00Z")
| SORT week

If the desired bucket size is known in advance, simply provide it as the second argument, leaving the range out:

FROM employees
| WHERE hire_date >= "1985-01-01T00:00:00Z" AND hire_date < "1986-01-01T00:00:00Z"
| STATS hires_per_week = COUNT(*) BY week = BUCKET(hire_date, 1 week)
| SORT week

BUCKET can also operate on numeric fields. For example, to create a salary histogram:

FROM employees
| STATS COUNT(*) by bs = BUCKET(salary, 20, 25324, 74999)
| SORT bs

Unlike the earlier example that intentionally filters on a date range, you rarely want to filter on a numeric range. You have to find the min and max separately. ES|QL doesn’t yet have an easy way to do that automatically.

The range can be omitted if the desired bucket size is known in advance. Simply provide it as the second argument:

FROM employees
| WHERE hire_date >= "1985-01-01T00:00:00Z" AND hire_date < "1986-01-01T00:00:00Z"
| STATS c = COUNT(1) BY b = BUCKET(salary, 5000.)
| SORT b

Create hourly buckets for the last 24 hours, and calculate the number of events per hour:

FROM sample_data
| WHERE @timestamp >= NOW() - 1 day and @timestamp < NOW()
| STATS COUNT(*) BY bucket = BUCKET(@timestamp, 25, NOW() - 1 day, NOW())

Examples

Create monthly buckets for the year 1985, and calculate the average salary by hiring month:

FROM employees
| WHERE hire_date >= "1985-01-01T00:00:00Z" AND hire_date < "1986-01-01T00:00:00Z"
| STATS AVG(salary) BY bucket = BUCKET(hire_date, 20, "1985-01-01T00:00:00Z", "1986-01-01T00:00:00Z")
| SORT bucket

BUCKET may be used in both the aggregating and grouping part of the STATS …​ BY …​ command provided that in the aggregating part the function is referenced by an alias defined in the grouping part, or that it is invoked with the exact same expression:

FROM employees
| STATS s1 = b1 + 1, s2 = BUCKET(salary / 1000 + 999, 50.) + 2 BY b1 = BUCKET(salary / 100 + 99, 50.), b2 = BUCKET(salary / 1000 + 999, 50.)
| SORT b1, b2
| KEEP s1, b1, s2, b2

Conditional functions return one of their arguments by evaluating in an if-else manner. ES|QL supports these conditional functions:

Syntax

CASE(condition1, value1[, ..., conditionN, valueN][, default_value])

Parameters

Description

Accepts pairs of conditions and values. The function returns the value that belongs to the first condition that evaluates to true.

If the number of arguments is odd, the last argument is the default value which is returned when no condition matches. If the number of arguments is even, and no condition matches, the function returns null.

Example

Determine whether employees are monolingual, bilingual, or polyglot:

FROM employees
| EVAL type = CASE(
    languages <= 1, "monolingual",
    languages <= 2, "bilingual",
     "polyglot")
| KEEP emp_no, languages, type

Calculate the total connection success rate based on log messages:

FROM sample_data
| EVAL successful = CASE(
    STARTS_WITH(message, "Connected to"), 1,
    message == "Connection error", 0
  )
| STATS success_rate = AVG(successful)

Calculate an hourly error rate as a percentage of the total number of log messages:

FROM sample_data
| EVAL error = CASE(message LIKE "*error*", 1, 0)
| EVAL hour = DATE_TRUNC(1 hour, @timestamp)
| STATS error_rate = AVG(error) by hour
| SORT hour

Syntax

COALESCE(expression1 [, ..., expressionN])

Parameters

Description

Returns the first of its arguments that is not null. If all arguments are null, it returns null.

Example

ROW a=null, b="b"
| EVAL COALESCE(a, b)

Syntax

Parameters

Description

Returns the maximum value from multiple columns. This is similar to MV_MAX except it is intended to run on multiple columns at once.

Supported types

Example

ROW a = 10, b = 20
| EVAL g = GREATEST(a, b)

Syntax

Parameters

Description

Returns the minimum value from multiple columns. This is similar to MV_MIN except it is intended to run on multiple columns at once.

Supported types

Example

ROW a = 10, b = 20
| EVAL l = LEAST(a, b)

ES|QL supports these date-time functions:

Syntax

Parameters

Description

Subtracts the startTimestamp from the endTimestamp and returns the difference in multiples of unit. If startTimestamp is later than the endTimestamp, negative values are returned.

Note that while there is an overlap between the function’s supported units and ES|QL’s supported time span literals, these sets are distinct and not interchangeable. Similarly, the supported abbreviations are conveniently shared with implementations of this function in other established products and not necessarily common with the date-time nomenclature used by Elasticsearch.

Supported types

Example

ROW date1 = TO_DATETIME("2023-12-02T11:00:00.000Z"), date2 = TO_DATETIME("2023-12-02T11:00:00.001Z")
| EVAL dd_ms = DATE_DIFF("microseconds", date1, date2)

Syntax

DATE_EXTRACT(date_part, date)

Parameters

Description

Extracts parts of a date, like year, month, day, hour.

Examples

ROW date = DATE_PARSE("yyyy-MM-dd", "2022-05-06")
| EVAL year = DATE_EXTRACT("year", date)

Find all events that occurred outside of business hours (before 9 AM or after 5 PM), on any given date:

FROM sample_data
| WHERE DATE_EXTRACT("hour_of_day", @timestamp) < 9 AND DATE_EXTRACT("hour_of_day", @timestamp) >= 17

Syntax

DATE_FORMAT([format,] date)

Parameters

Description

Returns a string representation of a date, in the provided format.

Example

FROM employees
| KEEP first_name, last_name, hire_date
| EVAL hired = DATE_FORMAT("YYYY-MM-dd", hire_date)

Syntax

DATE_PARSE([format,] date_string)

Parameters

Description

Returns a date by parsing the second argument using the format specified in the first argument.

Example

ROW date_string = "2022-05-06"
| EVAL date = DATE_PARSE("yyyy-MM-dd", date_string)

Syntax

Parameters

Description

Rounds down a date to the closest interval.

Supported types

Examples

FROM employees
| KEEP first_name, last_name, hire_date
| EVAL year_hired = DATE_TRUNC(1 year, hire_date)

Combine DATE_TRUNC with STATS ... BY to create date histograms. For example, the number of hires per year:

FROM employees
| EVAL year = DATE_TRUNC(1 year, hire_date)
| STATS hires = COUNT(emp_no) BY year
| SORT year

Or an hourly error rate:

FROM sample_data
| EVAL error = CASE(message LIKE "*error*", 1, 0)
| EVAL hour = DATE_TRUNC(1 hour, @timestamp)
| STATS error_rate = AVG(error) by hour
| SORT hour

Syntax

Parameters

Description

Returns current date and time.

Supported types

Examples

ROW current_date = NOW()

To retrieve logs from the last hour:

FROM sample_data
| WHERE @timestamp > NOW() - 1 hour

ES|QL supports these IP functions:

Syntax

CIDR_MATCH(ip, block1[, ..., blockN])

Parameters

Description

Returns true if the provided IP is contained in one of the provided CIDR blocks.

Example

FROM hosts
| WHERE CIDR_MATCH(ip1, "127.0.0.2/32", "127.0.0.3/32")
| KEEP card, host, ip0, ip1

ES|QL supports these mathematical functions:

Syntax

Parameters

Description

Returns the absolute value.

Supported types

Examples

ROW number = -1.0
| EVAL abs_number = ABS(number)

FROM employees
| KEEP first_name, last_name, height
| EVAL abs_height = ABS(0.0 - height)

Syntax

Parameters

Description

Returns the arccosine of n as an angle, expressed in radians.

Supported types

Example

ROW a=.9
| EVAL acos=ACOS(a)

Syntax

Parameters

Description

Returns the arcsine of the input numeric expression as an angle, expressed in radians.

Supported types

Example

ROW a=.9
| EVAL asin=ASIN(a)

Syntax

Parameters

Description

Returns the arctangent of the input numeric expression as an angle, expressed in radians.

Supported types

Example

ROW a=12.9
| EVAL atan=ATAN(a)

Syntax

Parameters

Description

The angle between the positive x-axis and the ray from the origin to the point (x , y) in the Cartesian plane, expressed in radians.

Supported types

Example

ROW y=12.9, x=.6
| EVAL atan2=ATAN2(y, x)

Syntax

Parameters

Description

Round a number up to the nearest integer.

Supported types

Example

ROW a=1.8
| EVAL a=CEIL(a)

Syntax

Parameters

Description

Returns the cosine of an angle.

Supported types

Example

ROW a=1.8
| EVAL cos=COS(a)

Syntax

Parameters

Description

Returns the hyperbolic cosine of an angle.

Supported types

Example

ROW a=1.8
| EVAL cosh=COSH(a)

Syntax

Parameters

Description

Returns Euler’s number.

Supported types

Example

ROW E()

Syntax

Parameters

Description

Round a number down to the nearest integer.

Supported types

Example

ROW a=1.8
| EVAL a=FLOOR(a)

Syntax

Parameters

Description

Returns the logarithm of a value to a base. The input can be any numeric value, the return value is always a double. Logs of zero, negative numbers, and base of one return null as well as a warning.

Supported types

Examples

ROW base = 2.0, value = 8.0
| EVAL s = LOG(base, value)

row value = 100
| EVAL s = LOG(value);

Syntax

Parameters

Description

Returns the logarithm of a value to base 10. The input can be any numeric value, the return value is always a double. Logs of 0 and negative numbers return null as well as a warning.

Supported types

Example

ROW d = 1000.0
| EVAL s = LOG10(d)

Syntax

Parameters

Description

Returns Pi, the ratio of a circle’s circumference to its diameter.

Supported types

Example

ROW PI()

Syntax

Parameters

Description

Returns the value of base raised to the power of exponent.

Supported types

Examples

ROW base = 2.0, exponent = 2
| EVAL result = POW(base, exponent)

The exponent can be a fraction, which is similar to performing a root. For example, the exponent of 0.5 will give the square root of the base:

ROW base = 4, exponent = 0.5
| EVAL s = POW(base, exponent)

Syntax

Parameters

Description

Rounds a number to the specified number of decimal places. Defaults to 0, which returns the nearest integer. If the precision is a negative number, rounds to the number of digits left of the decimal point.

Supported types

Example

FROM employees
| KEEP first_name, last_name, height
| EVAL height_ft = ROUND(height * 3.281, 1)

Syntax

Parameters

Description

Returns the sign of the given number. It returns -1 for negative numbers, 0 for 0 and 1 for positive numbers.

Supported types

Example

ROW d = 100.0
| EVAL s = SIGNUM(d)

Syntax

Parameters

Description

Returns ths Sine trigonometric function of an angle.

Supported types

Example

ROW a=1.8
| EVAL sin=SIN(a)

Syntax

Parameters

Description

Returns the hyperbolic sine of an angle.

Supported types

Example

ROW a=1.8
| EVAL sinh=SINH(a)

Syntax

Parameters

Description

Returns the square root of a number. The input can be any numeric value, the return value is always a double.

Square roots of negative numbers are NaN. Square roots of infinites are infinite.

Supported types

Example

ROW d = 100.0
| EVAL s = SQRT(d)

Syntax

Parameters

Description

Returns the Tangent trigonometric function of an angle.

Supported types

Example

ROW a=1.8
| EVAL tan=TAN(a)

Syntax

Parameters

Description

Returns the Tangent hyperbolic function of an angle.

Supported types

Example

ROW a=1.8
| EVAL tanh=TANH(a)

Syntax

Description

Returns the ratio of a circle’s circumference to its radius.

Example

ROW TAU()

ES|QL supports these spatial functions:

Syntax

Parameters

Description

Returns true if two geometries intersect. They intersect if they have any point in common, including their interior points (points along lines or within polygons). This is the inverse of the ST_DISJOINT function. In mathematical terms: ST_Intersects(A, B) ⇔ A ⋂ B ≠ ∅

Supported types

Example

FROM airports
| WHERE ST_INTERSECTS(location, TO_GEOSHAPE("POLYGON((42 14, 43 14, 43 15, 42 15, 42 14))"))

Syntax

Parameters

Description

Returns whether the two geometries or geometry columns are disjoint.

This is the inverse of the ST_INTERSECTS function. In mathematical terms: ST_Disjoint(A, B) ⇔ A ⋂ B = ∅

Supported types

Example

FROM airport_city_boundaries
| WHERE ST_DISJOINT(city_boundary, TO_GEOSHAPE("POLYGON((-10 -60, 120 -60, 120 60, -10 60, -10 -60))"))
| KEEP abbrev, airport, region, city, city_location

Syntax

Parameters

Description

Returns whether the first geometry contains the second geometry.

This is the inverse of the ST_WITHIN function.

Supported types

Example

FROM airport_city_boundaries
| WHERE ST_CONTAINS(city_boundary, TO_GEOSHAPE("POLYGON((109.35 18.3, 109.45 18.3, 109.45 18.4, 109.35 18.4, 109.35 18.3))"))
| KEEP abbrev, airport, region, city, city_location

Syntax

Parameters

Description

Returns whether the first geometry is within the second geometry.

This is the inverse of the ST_CONTAINS function.

Supported types

Example

FROM airport_city_boundaries
| WHERE ST_WITHIN(city_boundary, TO_GEOSHAPE("POLYGON((109.1 18.15, 109.6 18.15, 109.6 18.65, 109.1 18.65, 109.1 18.15))"))
| KEEP abbrev, airport, region, city, city_location

Syntax

Parameters

Description

Extracts the x coordinate from the supplied point. If the points is of type geo_point this is equivalent to extracting the longitude value.

Supported types

Example

ROW point = TO_GEOPOINT("POINT(42.97109629958868 14.7552534006536)")
| EVAL x =  ST_X(point), y = ST_Y(point)

Syntax

Parameters

Description

Extracts the y coordinate from the supplied point. If the points is of type geo_point this is equivalent to extracting the latitude value.

Supported types

Example

ROW point = TO_GEOPOINT("POINT(42.97109629958868 14.7552534006536)")
| EVAL x =  ST_X(point), y = ST_Y(point)

ES|QL supports these string functions:

Syntax

CONCAT(string1, string2[, ..., stringN])

Parameters

Description

Concatenates two or more strings.

Example

FROM employees
| KEEP first_name, last_name
| EVAL fullname = CONCAT(first_name, " ", last_name)

Syntax

Parameters

Description

Returns a boolean that indicates whether a keyword string ends with another string.

Supported types

Example

FROM employees
| KEEP last_name
| EVAL ln_E = ENDS_WITH(last_name, "d")

Syntax

Parameters

Description

Decode a base64 string.

Supported types

Example

row a = "ZWxhc3RpYw=="
| eval d = from_base64(a)

Syntax

Parameters

Description

Returns the substring that extracts length chars from string starting from the left.

Supported types

Example

FROM employees
| KEEP last_name
| EVAL left = LEFT(last_name, 3)
| SORT last_name ASC
| LIMIT 5

Syntax

LENGTH(str)

Parameters

Description

Returns the character length of a string.

Example

FROM employees
| KEEP first_name, last_name
| EVAL fn_length = LENGTH(first_name)

Syntax

Parameters

Description

Returns an integer that indicates the position of a keyword substring within another string. Returns 0 if the substring cannot be found. Note that string positions start from 1.

Supported types

Syntax

Parameters

Description

Removes leading whitespaces from strings.

Supported types

Example

ROW message = "   some text  ",  color = " red "
| EVAL message = LTRIM(message)
| EVAL color = LTRIM(color)
| EVAL message = CONCAT("'", message, "'")
| EVAL color = CONCAT("'", color, "'")

Syntax

Parameters

Description

The function substitutes in the string str any match of the regular expression regex with the replacement string newStr.

If any of the arguments is null, the result is null.

Supported types

Example

This example replaces any occurrence of the word "World" with the word "Universe":

ROW str = "Hello World"
| EVAL str = REPLACE(str, "World", "Universe")
| KEEP str

Syntax

Parameters

Description

Return the substring that extracts length chars from str starting from the right.

Supported types

Example

FROM employees
| KEEP last_name
| EVAL right = RIGHT(last_name, 3)
| SORT last_name ASC
| LIMIT 5

Syntax

Parameters

Description

Removes trailing whitespaces from strings.

Supported types

Example

ROW message = "   some text  ",  color = " red "
| EVAL message = RTRIM(message)
| EVAL color = RTRIM(color)
| EVAL message = CONCAT("'", message, "'")
| EVAL color = CONCAT("'", color, "'")

Parameters

Description

Splits a single valued string into multiple strings.

Supported types

Example

ROW words="foo;bar;baz;qux;quux;corge"
| EVAL word = SPLIT(words, ";")

Syntax